Lincode
Founded 2017 · 59 employees on LinkedIn · 6 known investors
Lincode builds LIVIS, an AI-based visual inspection system for manufacturing quality control that lets factory teams train and deploy computer vision models for surface defect detection, assembly verification, and anomaly detection through a no-code interface. It serves manufacturers and supply chain partners across industries such as automotive, aerospace and defense, electronics, semiconductors, printing and packaging, and food and beverage.
Also known as Lincode Intelligent Visual Inspection System · LIVIS
Founders & leadership
Lincode was founded in 2017 by Rajesh Iyengar.
Investors · 6
Company profile
researched Aug 2026Lincode develops the Lincode Intelligent Visual Inspection System (LIVIS), a proprietary AI-based visual inspection product for manufacturing quality control. LIVIS performs real-time quality inspection of parts in production using deep learning models rather than rule-based machine vision logic, and is positioned to address limitations the company attributes to traditional systems, such as high false-call rates, the need for secondary inspections, dependence on controlled environments, and limited data tracking. The system supports surface defect detection and classification (including foreign objects and debris), assembly verification for component presence, orientation and alignment, and unsupervised anomaly detection intended to flag untrained defects when they first appear. Label inspection is also cited as a capability.
Every LIVIS deployment includes two software applications. LIVIS Edge+ is the runtime component that runs AI inference at the edge on the production line, integrating with industrial cameras and factory automation systems, and connecting to PLC, MES, ERP and other factory control systems. It captures images, inspection results, timestamps and unique identifiers to support data traceability and regulatory compliance. LIVIS Platform is the model-training and inspection-workstation management layer, offering a no-code interface through which factory managers, engineers and operators can train custom inspection recipes, called AI Inspectors, and deploy them to multiple LIVIS Edge+ instances. The AI Inspector module combines pre-trained models, curated annotated training datasets and pre-configured business logic into deployable solutions for specific inspection tasks. The platform can be run in the cloud or on premises and provides dashboards covering real-time results, defect trends and other analytics.
The company states that LIVIS Platform draws on more than 700 AI models pre-trained on over 800 million data points, that new parts and defects can typically be trained with 30-50 images, that real-time analysis averages under 40 milliseconds, and that auto-annotation is used to speed up new deployments. Lincode states it is SOC 2 compliant.
Business model
Lincode sells software: the LIVIS Edge+ runtime application and the LIVIS Platform training and management application, which are included together in each deployment and can be run on premises or via the cloud. The product is hardware-agnostic and is designed to work with a customer's existing industrial cameras, positioning it for both brownfield and greenfield installations without hardware replacement.
▸Full profile — market position, technology, go-to-market
Market position
Lincode positions LIVIS against two alternatives: traditional rule-based machine vision systems, which it characterizes as prone to false calls, secondary inspections and reliance on controlled environments; and general-purpose AI platforms, which it characterizes as requiring large training datasets, long training cycles and significant investment, leading to stalled pilots. It claims LIVIS outperforms both on accuracy, latency and deployment speed.
The company's stated differentiators are pre-trained, manufacturing-specific AI models that cut data and training requirements, a no-code interface allowing factory staff rather than data scientists to create and deploy inspection models, hardware-agnostic integration with existing cameras and factory control systems, edge inference with sub-40ms average latency, and end-to-end data traceability through captured images, results, timestamps and unique identifiers.
Technology
LIVIS is built on deep learning rather than rule-based machine vision. It ships with proprietary models pre-trained on industry- and use-case-specific manufacturing datasets, reported as 700+ models trained on 800M+ data points, which the company says reduces the data needed to train a new part or defect to roughly 30-50 images on average. Inference runs at the edge via LIVIS Edge+, with average analysis times under 40 milliseconds. Unsupervised learning models are used for anomaly detection of untrained defects, and auto-annotation plus continuous learning of new parts and defects are supported. Integrations cover industrial cameras from any provider and factory systems including PLC, MES and ERP.
Go-to-market
Manufacturers and their supply chain partners performing quality inspection on production lines. Named users within those organizations include manufacturing engineers, machine operators, quality managers and factory managers.
Compiled by commissioned research from 1 cited public sources — announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed — not independently audited.
▸Research sources · 1
primary sources listed
- Lincodelincode.ai · web
1 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Lincode do?
- Lincode builds LIVIS, an AI-based visual inspection system for quality control on manufacturing production lines.
- Who founded Lincode?
- Lincode was founded by Rajesh Iyengar in 2017.
- Who are Lincode's investors?
- Lincode's investors include Alumni Ventures, Arka Venture Labs, Basecamp Fund, Expert DOJO, Geek Ventures, Augment Ventures.